structured products in equity market

8/7/2019 Structured Products in Equity Market

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Research Paper

For

National Stock Exchange

On

Imbalances Created because of Structured Products

in Indian Equity markets

By

GopiKrishna Suvanam & Amit Trivedi


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Imbalances Created by Structured Products National Stock Exchange in Indian Equity

markets

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Abstract

This paper is study of effect of hedging of structured products on exchange traded equity products. We

look at various aspects of the structured product markets including the motivation to buy, the risks ofthe products, the hedging behavior and the effect of hedging on exchange traded products. We

conclude the hedging would be volatility supportive in a sell off and would be volatility suppressing in

significant rally. We also suggest introduction of some new exchange products that would make the

hedging process easy and also would help some retail investors express their view in a better fashion

without the transaction costs involved in structured products.


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Table of Contents

Abstract 1

Introduction 4

Composition of the Structured Product Market 5

Evolution of Structured Notes in India 12

Framework for Analysis 13

Pricing and Modeling 17

Risks of Each Product 19

Aggregation of Risks 22

Effect on Exchange Traded Products 25

New Products 26


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Introduction

Derivative trading is essential tool for the health of markets as they enhance price discovery and

supplement liquidity. Although derivatives have been introduced very late in Indian equity markets they

picked up prominence very quickly. In June 2000, index futures were introduced as the first exchange

traded equity derivative product in the Indian markets. In a span of a year and a half after that index

options, stock options and lastly stock futures were introduced. Since then, derivatives volumes have

grown to multiples of cash market volumes and have been a mode of speculation and hedging for

market participants, not possible otherwise through cash markets.

In 2007, Statistics from the NSE show that retail investors have been the largest participants in the

derivatives markets in the past four-five years, accounting, on average, for around 60 per cent of all

derivatives based activity.

Although derivatives are good instruments to expresses complex non linear views on markets, lack of

sophistication and understanding has given rise to investments into structured products, which have

derivative like payoffs but are bespoke and not exchange traded.

With the advent of structured products, many retail and HNI investors have been able to invest for more

exotic payoffs compared to linear payoff they used to realize from their cash investments. In 2007, there

were numerous institutions offering structured products to their clients and that has lead to growth ofthe institutional presence in derivatives segment. While the investor invests for a certain period, the

issuer of the product constantly uses derivatives segment to hedge his positions to create the desired

payoff for its clients.

Before the arrival of structured products the main avenues of investment for individual investors have

been either investing directly in stocks or equity based mutual funds or in certain cases investing in fixed

income securities like corporate and government bonds. Structured products have been created as an

alternative to directly investing in underlying asset to give additional benefits to the investor.

The benefits of structured products include:

principal protection diversification benefits (if the product is linked to an index or a basket of securities) tax-efficient access to fully taxable investments


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enhanced returns within an investment reduced volatility (or risk) within an investment express specific view of the investor

Unlike other exchange traded securities and derivatives, structured products are by nature not

homogeneous - as the variety of underlying, payoff structure and maturities can vary significantly. The

underlying instruments in structured products can however be broadly classified under the following

categories

Equity-linked Notes & Deposits Interest rate-linked Notes & Deposits FX and Commodity-linked Notes & Deposits Hybrid-linked Notes & Deposits Credit Linked Notes & Deposits Market Linked Notes & Deposits

Although structured products and OTC derivatives can be traded on a variety of asset classes the scope

of this paper is to study the structured products linked to Equities. Now on when we say Structured

Products it is to be assumed that we refer to the products linked to equity only.

Composition of the Structured Product Market

Prudential ICICI introduced India's first capital-protected constant proportion portfolio insurance (CPPI)

product for Indian investors, dubbed the Principal Protected Portfolio (PPP). Developed with Deutsche

Bank in London, the product was one of the biggest innovations to hit the Indian market

Prudential ICICI's CPPI has since been copied by a host of other issuers keen to tap the demand for

principal protection. Typically, these products are issued within the portfolio management services

(PMS) line offered by banks to their high-net-worth clients, although the growing appeal of capital

protection has also seen the CPPI structure filtering into retail market. Subsequent to that another

major development has been the issuance of structured products in note format, created using

'synthetic' options. The first of these was issued by Standard Chartered and structured by Merrill Lynch,

offering investors an option-based payoff. The synthetic options are hedged by dealers with


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international branches and issued in debenture format1. As demand for these products developed the

market saw several issuers coming up with a range of products to suit the needs of the investors.

Currently the suite of products available for investors is very rich in variety and innovation.

The existing structured products in the equity space can be broadly classified into the following

categories:

Equity linked notes (debentures) with capital protection CPPI and related structures Range accruals on Equity index/basket of stocks Autocallable notes and other exotic structures Structured on baskets of stocks

In this section we give a brief description of each of the products to enable the reader grasp the payoff

of these structures. We also discuss the motivation behind investing in each of the products.

Equity Linked Debentures

An Equity-Linked Note (ELN) is an instrument that provides investors fixed income like principal

protection together with equity market upside exposure. Capital protected equity linked notes are

about the most prevalent of the structured products and constitute about 90% of the market in Indian

equity linked structured products. Hence we devote significant part of this section and the future

sections discussing various aspects of these notes.

The investment structure generally provides 100% principal protection, which means the capital of the

investor is returned back at maturity. The coupon at maturity on the other hand is variable and is

determined by the appreciation of the underlying equity. The payoff of a simple structured product with

capital protection is juxtaposed with the payoff of investing in the underlying in the chart below.2 By

giving up part of upside (participation in upside is typically less than 100%) the investor gets a protection

against downside. The instrument is appropriate for conservative equity investors or fixed income

investors who desire equity exposure with controlled risk.

1Structured Products A Positive Correction:

http://www.structuredproductsonline.com/public/showPage.html?page=4304822

The charts displayed in this section are for the purpose of illustration alone and do not correspond to actually

market prices.


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As an example of an ELN, assume an investor buys a hypothetical five-year 100% principal protected

Equity-Linked Note with 80% participation in the upside of the S&P Nifty Index for Rs. 1,000. The starting

index level is 4000. At maturity, if the S&P Nifty Index level is above 4000, then the payoff of the note

will be Rs. 1,000 in principal plus an equity-linked coupon equivalent to any increase in the index. For

example, if the index level in five years is 5000 (an appreciation of 25%), then the coupon would be Rs.

200 (80%*25%*1,000) and the total payoff would be Rs. 1,200 (1,000 + 200).

If the index level is below 4000 at maturity, i.e., the underlying equity performance is negative, the final

payoff to the investor will be Rs. 1,000 in principal.

An ELN is structured by combining the economics of a long call option on equity with a long discount

bond position.

Bond + Call Option => Equity Linked Note => Principal Protection + Equity Participation


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Participations of more than 100% can be achieved by capping the upside beyond a certain level. In this

case the payoff of the client linearly increases if at maturity the underlying is more than at the start of

the product but after certain level the profits become flat. The chart below illustrates the payoff of such

a product.

In this case the ELN is equivalent to a zero coupon bond plus a long ATM call and short position in high

strike call.


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Bond + Call Option High strike call option => Principal Protection + Equity Participation with a

cap

Opportunity Cost: Although ELNs repay an investor their principal at maturity, there is an opportunity

cost even where an investor receives a return of principal in down markets; i.e., that investor has lost

the use of his/her invested principal for the term of the ELN (in an investment in a risk-free asset like

bank fixed deposit).

Call-trigger: The structures normally also have a call feature embedded within them which enables the

issuer to call back the note if the underlying sells of by more than a trigger amount (typically 50%) from

the start value. In this case the investor gets back only his principal at the end of maturity irrespective of

how the underlying behaves once the trigger level is breached.

Factors affecting Price of an ELN

Increase in Equity Price (+)

Increase in Volatility (+)

Increase in Interest rates (-)

Increase in Time to Expiration (+/-)

Increase in Dividend Yield (-)

Issuers Credit Rating (+)

CPPI/DPI

Equity linked debenture attains capital protection by replicating a call option pay off. The other way to

achieve capital protection is by dynamically managing a portfolio so that the investor always has the

money to buy a zero coupon bond, providing the money for capital payback at maturity. For example,

say an investor has a portfolio of Rs. 100, a floor of Rs. 90 (price of the bond to guarantee his RS. 100 at

maturity) and a multiplier of 5 (ensuring protection against a drop of at most 20% before rebalancing

the portfolio). Then on day 1, the writer will allocate (5 * (100 - 90)) = Rs. 50 to the risky asset and the

remaining Rs. 50 to the riskless asset (the bond). The exposure will be revised as the portfolio value


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changes, i.e. when the risky asset performs or sells off. These rules are predefined and agreed once and

for all during the life of the product.3

A variant to CPPI is DPI (Dynamic Portfolio Insurance) where the multiplier is not specified upfront but

varies according to certain parameters like the volatility of the underlying.

The exposure to risky asset is completely unwound if the portfolio value falls below the bond floor. The

bond floor is the value below which the CPPI value should never fall in order to be able to ensure

nationals guarantee at maturity. Bond floor is a function of time to maturity and interest rates. As

interest rates fall, bond floor goes up because to ensure payment of principal at maturity one needs

more cash upfront if interest rates are lower than if they are higher. Executing a CPPI would involve

buying when the underlying rallies and selling when the underlying sells off. This process would further

accentuate the market volatility as the hedging goes in the same direction as the market movement.

RangeAccruals

Range accrual security is a kind of structured product where the interest is accrued only on days when

the underlying equity/index is within a range. The capital is protected in most structures only the

interest/coupon is variable. The coupon of the range accrual is paid according to a pre-agreed formula:

The fixed % and the range are agreed at the start of the investment. The observation days could be

daily, monthly, quarterly or even a single observation at the maturity of the product. Products with

single observation at the maturity have been the most popular amongst range accrual notes. In this case

the coupon is digital, as in if the underlying ends up within the range the investor gets a fixed coupon or

else he just gets his principal back. The chart below shows the payoff of range accrual note for various

values of underlying.

3Constant proportion portfolio insurance and the synthetic put option : a comparison, in Institutional Investor

focus on Investment Management, Black, F., & Rouhani, R. (1989)


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Auto-callable notes and other structures

The structures described above are aimed to get a capital protection plus some upside at the end of

maturity depending on the value of underlying at maturity. More exotic structures offer payoffs linked

to the path taken by underlying. Most typical of these are auto-callable notes. These notes are auto-

called or redeemed by paying principal and a coupon if the underlying appreciates beyond a certain level

anytime during the tenure of the note. If the underlying does not reach the auto-call level anytime

before the maturity the principal is returned back. Auto-callable notes are equivalent to knock-

out/knock-in barrier options in the OTC derivatives space. Once the note is called the payoff does not

depend on future price of the underlying.

Auto-callable notes can be used for positioning for an appreciation or a sell-off in the underlying,

although most of the structures prevalent in India position for a rally. Other exotic payoffs can also be

structured like for example structures paying out coupon linked to maximum value of the underlying

during the tenure. For more aggressive investors products have been offered where the investor takes

downside risk if the underlying sells of beyond a certain level.

Although structured products are highly popular on indices some structures have been executed on

baskets of stocks as well. These kinds of structures form about 1-2% of the total market of structured

products. Although introducing baskets of stocks would add variety to the product suite offered by the

issuer the hedging of such products becomes extremely cumbersome.


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Though discussion on these products would be interesting and intellectually stimulating they do not

matter much in terms of market share effect on Indian equity markets.

Evolution of Structured Notes in IndiaAlthough there are no concrete numbers available, the structured product industry is estimated to

house products worth more than Rs 10,000 crore, with Citigroup, Merrill Lynch and Kotak accounting for

a sizeable chunk of the market4

Prior to May 2005, issuers had been prohibited from explicitly marketing capital-protected products to

investors. In August, however, partly as a result of the stock market falls SEBI relaxed these rules

allowing issuers to offer funds with a rating agency seal of approval5

The CPPI structures executed in

India are mostly PMS based trading strategies without explicit guarantee of capital return. The capital is

guaranteed through dynamically managing the portfolio and when the bond-floor (the minimum

amount required to return capital at the maturity) is hit the strategy is liquidated and the proceeds are

returned to the investor or invested in risk-free securities. As volatility in the markets increased in 2007

some of the CPPI products issued earlier got monetized in 2007. Most of the remaining structures got

unwound in 2008 when markets fell significantly and bond prices went up (because of fall in interest

rates).

Next wave of structured products came in the form of simple capital guaranteed structures withparticipation in the upside. These structures were very popular in the first half of 2007 when markets

were exhibiting volatility. Initially the participation was around 90% with no cap on upside or very high

cap. But as the markets sold off significantly in 2008 investors preferred more participation in the upside

with a cap. Range accruals were also prevalent around that time as investors did not see much upside or

downside in equity markets and as a result of high interest rates they preferred fixed coupon if the

market remained in a range.

4

http://economictimes.indiatimes.com/News/News_By_Industry/Banking_Finance_/Finance/Structured_products_

face_heat_now/articleshow/3496022.cms5

Structured Products A Positive Correction:

http://www.structuredproductsonline.com/public/showPage.html?page=430482


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The table below shows typical characteristics of the popular structured products based on a survey we

conducted amongst the top issuers in this space6. Capital guaranteed participation notes and range

accruals command about 93% of market share. Although CPPI structures constituted 5% of the total

trades, as discussed earlier most of these structures have been unwound. More exotic structures are

miniscule part of the total market. Hence we will focus on the first two classes of products for further

discussions.

Framework for Analysis

In this section we establish the framework required to understand the effect of structured products on

equity markets. For the investor the payoff of a structured product is clear and he would be taking an

outright view on the underlying and use the product to either express the view or to try to enhance his

yields or to reduce his risks. An issuer of the product on the other hand does not desire to take outright

view on the underlying. He would try to hedge away most of his exposure through various tradable

instruments. This process of hedging transfers the risks he has to the broader equity market. We analyze

this transfer mechanism to study the effect of the issuance of these products on Indian equity markets.

For this purpose we use the following notations. These are the terminology that will help decipher the

behavior of structured product issuers. These indicators of risk are also called Greeks as Greek letters

are used to represent them.

Delta: Delta is the rate of change in the price of structured product with respect to change in the

underlying. We further classify delta into initial delta and subsequent delta.

6The participants request anonymity


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Initial Delta: Every product when issued creates an exposure to the underlying for the investor. For

example when a capital protected participation note is issued the issuer has a short exposure in the

underlying. Thus to hedge the position the issuer needs to create a long position in the underlying

security (though not to the same extent as the notional of the note) either through cash market or

derivatives market (futures/calls). This would create a demand for the underlying.

Dynamic Delta: Even after putting in place the initial hedge the issuer is not completely hedged from the

movements of underlying because of the non-linear nature of structured products. The delta of the

structured product changes as the underlying moves. These changes have to be constantly hedged using

derivatives. Once we model the structured note using a theoretical model we can come up with the

exposure as the underlying moves. For example the chart below shows the delta of capital guaranteed

note for different underlying movements. Change in delta would mean the dealer has to rehedge his

exposure by buying/selling the underlying.

Delta for different underlying moves for principal protected note7

It is worthwhile to note that as market rallies the dealer is forced to buy more of the underlying to

hedge his exposure and as market sells off the dealer would sell some of his hedge. Thus hedging of

principal protected note would accentuate the market volatility as the dealer buys in a rally and sells in a

7The graphs in this section are for illustration for more accurate graphs refer to subsequent sections.


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selloff. The profile of hedging would be different for range accruals. The graph below shows the delta for

a range accrual with a range of 80% - 125%.

Delta for different underlying moves for range accrual note

In the case of range accrual the dealer is forced to sell the hedge either in a huge rally or sell off, he

would hold to his initial hedge only if the underlying remained in the range. Thus hedging of a range

accrual would dampen volatility if the underlying is trading within the range and the hedging will

accentuate volatility if the underlying is trading outside the range.

Gamma: Gamma is the rate of change of delta with respect to change in underlying. Gamma of a

product can be hedged by taking opposite positions in options. Once the gamma is hedged frequent

delta hedges are not required as the changes in delta in structured products and the hedges cancel out

each other. But gamma hedging comes with a cost hence most players prefer dynamic delta hedging to

gamma hedging. Gamma of a capital protected structure is positive and is negative for a range accrual

(within range).

Gamma of the structured product is very relevant to understand the effect of delta hedging. If the

gamma of a product is positive then the gamma of the dealer/issuer who has the opposite exposure of

the structured product is negative and vice versa. Thus positive gamma of the product implies that the

hedging of the product would accentuate the volatility of the underlying and negative gamma means

that the hedging would dampen the volatility of the market. Gamma of a simple capital protected


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structure is the gamma of the call option embedded in the structure. This gamma can be theoretically

calculated using Black-Scholes formula. The gamma of the structured product under this assumption

would be

Where

And is the standard normal function

Because of the symmetry and the bell-like shape of the Gamma of a simple capital protected note

with equity participation would also be of the bell shape and the peak gamma is attained when the

underlying is close to the initial value as evident in the chart below:

Gamma for different underlying moves for a simple principal protected note8

8All the charts in this paper are for the notes held by the investor the risks of the issuer will be exactly opposite of

this


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The range accrual note on the other hand behaves differently compared to a capital protected note. The

gamma of the note is negative when the underlying is within the range. Maximum negative gamma is

attained when underlying is close to the middle of the range. As we move out of the range the gamma

switches sign from ve to +ve. Thus hedging of range accruals dampens volatility when underlying is

within the range and accentuates volatility when the underlying is outside the range.

Gamma for different underlying moves for range accrual note

Vega: Price of a non-linear structure not only changes with the underlying but also with the volatility of

the underlying. This exposure is called Vega. Vega can be hedged by taking opposite position in long

dated options. Long dated options are typically used to hedge the capital guarantee part of the

structures.

As we have seen in this section a simple analysis also gives insights into the effect of structured products

on market volatility. Until now we have used Black-Scholes framework, going forward we develop more

sophisticated pricing framework and use stylized market data to get more accurate analysis.

Pricing and Modeling

Given the knowledge of risks of the dealer and how they change with underlying movement we can

come up with educated guess on hedging behavior of the aggregated dealer community. Even though

this may not be extremely accurate (because of difference in modeling across dealers and presence of


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OTC market) we think this analysis would give more insights into the supply demand dynamics of the

derivatives market. For understanding the risks first step would be to model the securities and to set up

a pricing engine.

Although Black-Scholes formula is good enough for pricing simple derivatives advanced methods are

necessary for pricing structured products given the call-trigger embedded in most of the notes. For this

reason we developed Monet-Carlo simulation engine to price some of the typical structured notes for

various underlying and volatility assumptions. The engine prices the securities by assuming a geometric-

Brownian motion for the underlying. More complex models are used for pricing some exotic products

but for the purpose of understanding risks geometric-Brownian motion is an accurate assumption.9

Under the assumption of Brownian motion the underlying security is modeled as a random process:

Where W is a Wiener process or Brownian motion and ('the percentage drift') and ('the percentage

volatility') are constants. For small time steps one can generate a sequence of prices for the underlying

from the following equation:

Where is a normal variable with 0 mean and standard deviation 1. For different values ofN one can

obtain different paths for the underlying. We use simulate 30,000 such paths and get the payoff of the

security in each path. The average of the discounted payoffs over all the 30,000 paths gives the model

price of the security. The price is dependent on S (price of underlying), time to maturity and . Then we

repeat the process for various values of S to obtain the risk profile viz. delta and gamma for different

scenarios. For an example let us take a capital protected structure with the following characteristics:

Underlying Index Nifty

Index value at the time of Issuance 5500

9Applications of Monte Carlo Methods in Finance: Option Pricing, Y. Lai and J. Spanier:

http://www.smartquant.com/references/MonteCarlo/mc6.pdf


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Time to maturity (current) 18months

Capital Protected 100%

Participation 85%

Cap No Cap

For the purpose of this analysis we are assuming 32% annual volatility, which is the current implied

volatility of exchange traded options. Implied volatility is appropriate for this analysis as market

participants hedge based on implied volatilities. Although some numbers might change when implied

volatilities change but broad conclusions of this paper should be unchanged. The drift is assumed as

8%, the risk free interest rate. The current modeled price of the security as a percentage of initial value

for various assumptions of the index level is shown in the chart below:

Risks of Each Product

Once the pricing mechanism is set we proceed towards calculating delta as the slope of the graph at

each Nifty level. For the product described above we get a delta profile as expected from the discussions

in the previous sections. The delta profile is upward sloping and flattens out as we go out of the money

and plateaus at 85% (the upside participation parameter). The delta is expressed as a percentage of

original notional.


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Delta profile of Cap-guaranteed structure: Participation 85%, no cap

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

0 2000 4000 6000 8000 10000 12000Nifty L eve l

Delta

If we change the structure slightly by introducing a cap on the returns we get a delta profile different

from the above. The delta is still upward sloping when Nifty is close to initial value, but as we go closer

to the cap on participation it drops very fast and tends to zero on further rally. Thus in a rally, hedging of

this product would dampen volatility as opposed to accentuating.


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Delta profile of a Cap-guaranteed structure: Participation 120%, 150% cap

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

0 2000 4000 6000 8000 10000 12000Nifty L eve l

Delta

The delta profile of a range accrual also comes out similar to the Black-Scholes approximation. The delta

increases as Nifty falls from initial levels up until the lower barrier of the range. Once the Nifty breaches

the lower barrier delta starts dropping. The behavior of delta in a rally is the mirror image of this. Delta

keeps falling as nifty rallies until the upper barrier is crossed; beyond that delta starts increasing and

approaches 0. Hedging of the following product would dampen volatility if Nifty is in the range of 3000-

5000. For Nifty levels below 3000 and above 5000 the hedging would accentuate the volatility.


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Delta profile of a Range Accrual: 80% to 125% range

In this section we looked at the risks of individual products. In the next section we will focus on the

aggregated risks across all the products.

Aggregation of Risks

The table below shows delta values for structures issued in the past three years. The values are for

typical products on the basis of a survey done amongst primary issuers. Initially when the products were

issued the total delta would have been around 50% of the market size of structured products. This

would have amounted to buying demand from issuers to the amount of 5000crore notional in Nifty.

Currently almost all the products are trading at close to 0 delta. Thus as we sold off from the peak the

issuers are forced to unwind their hedge thus a supply of close to 5000crore notional in Nifty came from

the dynamic hedging of these products. This could have further accentuated the fall in the market. The

gamma of capital protected notes is positive (unless in the case of a huge rally). Thus hedging of these

products would have been one of the causes of market volatility. Also the gamma of range accruals at

the time of issuance would have been negative but as we sell off and nifty crosses the lower barrier

(which is around 20% lower than the level at the time of issuance) the gamma of the product flips sign

and becomes positive. Thus in a sell off the hedging of range accruals is also supportive of volatility.


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Table Summarizing Basic Risks of Each Product10

Although risks for individual products can be calculated but what affects the market is the combined

effect of hedging all the products. Hence for the purpose of analysis we look the aggregated risks of the

structured product universe. The first step to look at aggregated risks is to get aggregated delta of the

structured product universe. This we obtain by replicating the structured product universe with 5 typical

products. Of these 4 products are capital guaranteed structures with various tenures and characteristics.

These are assumed to make up upto 80% of the 10,000 crore market. We assume 13% to be consisting

of a typical range accrual. The rest of the 7% is assumed be consisting of CPPI kind of structures and

autocallable notes, most of which have been called back or monetized/unwound. Of all the risks the risk

hedged out first is delta risk. And this has the highest impact on the equity markets. The delta of each

product is calculated using monte-carlo simulation as described in the previous section. The aggregated

net delta is obtained by multiplying each delta with the assumed notional and adding up. This

aggregated delta profile of the structured product universe is a representative of the delta hedging

behavior of the issuers. The profile is shown below. The delta profile peaks around the nifty level of

4700 and falls on both sides (sell off and rally). In a sell off, the net effect of hedging puts further selling

pressure.

10The estimates are as of May 2010


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Aggregated Delta of All Structured Products Put Together

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

200,000

0 2000 4000 6000 8000 10000 1200Nifty L eve l

D

eltaintermsofnumberofniftys

hares

To understand the nature of delta we have to delve into gamma profile of the structured product

universe. Gamma profile can be obtained by taking the slope of the above curve. Gamma profile shows

the effect of hedging on volatility. The gamma of the structured product universe is positive for Nifty

levels below 4700 and flips sign for higher nifty levels. This indicates hedging of these products would be

a cause of increase in volatility if the level of Nifty is below 4700 and it would be a volatility suppressing

factor if the Nifty levels are above 4700. Peak gamma is attained around a Nifty level of 2200 and

gamma falls as nifty rallies/sells off from there. Thus is a rally hedging of structured products would

have a dampening effect on volatility of Nifty and in a sell off below 4700 the effect would be to

accentuate the volatilities.


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Aggregated Gamma of All Structured Products Put Together

-40

-20

0

20

40

60

80

100

0 2000 4000 6000 8000 10000 12000

Nifty L eve l

Gamma

In the survey we performed with the issuers we found out that most issuer do only delta hedging of

their exposures. Some issuers use long dated options to take off some of the volatility (gamma and

vega) exposure. But because of lack of liquid markets in this sector this strategy is not widely popular.

Shorter dated options are also not much used because of mismatch of maturities and negative carry

involved in using shorter dated options as typically long-term volatility is lower than the implied

volatility of shorter dated options.

Effect on Exchange Traded Products

In this section we summarize our findings on the effect of the hedging on some of the exchange traded

products.

Volatility of Nifty: Hedging has been supportive of volatility on nifty. In a huge rally this support might

wane and hedging could become volatility suppressing beyond 4700 Nifty level.

Nifty cash/futures basis: As futures are the preferred way of hedging, the volatility caused by hedging is

transferred more to the futures market than the cash market. Hence the futures could trade more

volatile than the cash market. This implies the futures could trade at huge discount in sell off and at a

premium in a rally.


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Short dated options: Although shorter dated options are not directly used by most of the issuers to

hedge their books, the higher realized volatility might translate into higher option prices/implied

volatility.

Long dated options: Longer dated options are used by some issuers to hedge their exposure, especially

for getting capital protection. This would cause a bid in longer expiry options (beyond one year expiry)

VIX: Having a long position in VIX can be used to hedge the short volatility exposure of the issuers

although the hedge is not that straight forward.

New Products

In this section we discuss some new products that could be introduced as exchange traded instruments

to ease the hedging needs of issuers of structured products. These products are not only useful for the

hedging needs of issuers but they can also be used by retail clients to express their views on equity

markets, avoiding transaction costs involved in structured products.

Digital Options: Unlike linear Puts/Calls which pay a linear pay off if the option is exercised, digital

options pay a fixed coupon if the strike condition is met. These options are a straightforward hedge to

the range accruals. Also these options are extremely useful expressing certain views on the underlying

(like a range bound view or a mild rally/sell off view etc). The payoffs of a linear and a digital call option

are juxtaposed in the chart below.

-5

0

5

10

15

20

25

30

35

60 70 80 90 100 110 120 130 140

Price of underlying

Payoff

Digital C all Option

L inear C all Option


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Variance Swaps/futures: Variance swap/future is an instrument to hedge/take exposure to the realized

volatility of the underlying. In this instrument one of the counterparties receives the floating leg which is

the variance of the underlying and pays a predetermined fixed price. The other counterparty pays the

variance and receives the fixed leg. Variance swaps are useful instruments to hedge Gamma exposure

without trading short-dated options.

Variance is a measure of how spread out a distribution of daily returns is. It is computed as the average

squared deviation of each days returns from its mean. An example of such a product in the developed

markets is the CBOE S&P 500 Three-Month Variance Futures. These are cash-settled, exchange-traded

futures contracts based on the realized variance of the S&P 500 Composite Stock Price Index11

. The

CBOE S&P 500 Three-Month Variance futures contract is quoted in terms of variance points. Variance

points are defined as realized variance multiplied by 10,000. For example, a variance calculation of

0.06335 would have a corresponding price quotation in variance points of 633.50.

A "continuously compounded" daily return (Ri) is calculated from two reference values, an initial value

(Pi) and a final value (Pi+1), using the following formula: Ri = ln(Pi+l/Pi). Daily returns are accumulated

over a three-month period, and then used in a standardized formula to calculate three-month variance.

This three-month value is then annualized assuming 252 business days per year:

=

=

1

1

2

1

*252

N

i

i

N

RV

Where N is the actual number of Nifty values used to calculate daily returns during the three-month

period.

Futures on VIX: Future contracts on Volatility Indices are extremely useful to hedge the volatility

exposure of structured products. These instruments are especially useful to hedge the Vega exposure as

VIX is directly linked to the implied volatility. An example of futures on volatility indices is the set of

CBOE DJIA Volatility Index (VXD) Futures.12

GAP risk swaps: The gap options are a class of exotic equity derivatives offering protection against rapid

downside market moves (gaps). The floating leg of these swaps is paid out if there is a huge move in the

underlying beyond a certain trigger/strike (lets say 10% downward move in a day). These options have

11CBOE S&P 500 3-month Variance Futures, Product Specifications: http://cfe.cboe.com/Products/Spec_VT.aspx

12Futures on the CBOE DJIA Volatility Index, A Quick Guide: http://www.cboe.com/micro/vxd/vxdqrg.pdf


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close to zero delta, allowing to make bets on large downside moves of the underlying without

introducing additional sensitivity to small fluctuations, just as volatility derivatives allow to make bets on

volatility without going short or long delta. The market for gap options is relatively new, and they are

known under many different names: gap options, crash notes, gap notes, daily cliquets, gap risk swaps

etc. The gap risk often arises in the context of constant proportion portfolio insurance (CPPI).13 The CCPI

market in India is in nascent stages and might see an increased interest from retail players if there is an

instrument available to hedge the Gap risk.

13Pricing and hedging gap risk, Peter Tankov: http://people.math.jussieu.fr/~tankov/gap_risk.pdf

structured products in equity market

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